Journals
2025 EN
Ely Fernando · Moreno Salvador · MinaryJolandan Majid
+5 more
Biopolymers are interesting technological platforms for green and eco‐friendly devices while enabling the desirable biocompatibility. Herein, micro‐ and nanostructures have been fabricated on the biopolymer collagen type I using thermo‐nanoimprinting lithography (T‐NIL) under relatively low temperature and applied pressure. The collagen samples are prepared by spin coating directly on substrates or as self‐standing membranes by casting from cosmetic‐grade ovine collagen acidic solutions. After NIL parameter optimization, complex microstructures and nanostructures can be realized at temperatures as low as 125 °C under an applied pressure of 50 bar for 300 s. The nanopatterns and eventual collagen macrostructure changes are completely characterized by optical microscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), thermal analysis, and spectroscopy techniques. The broad utility of such nanopatterns as Bragg gratings and plasmonic sensors is discussed.
Journals
2025 EN
Albar Norashikin · Anuar Sabiqah Tuan · Azmi Alyza Azzura
+6 more
Abstract The extensive use and disposal of various petroleum‐derived plastics has become a major cause of environmental pollution. The urgent need for sustainable materials to address plastic waste have resulted in the production of biodegradable plastics. In this study, a biodegradable plastic film is produced by incorporating chitosan with starch from Malaysian cassava ( Manihot esculenta ), utilizing the multihydroxyl properties of cassava starch. The results show that the addition of chitosan as a filler in cassava starch improves the physicochemical properties of the material, producing a bioplastic film with high compressive strength and resistance to water molecules. The contact angle of the developed biopolymer has been improved – from θ = 67.4° to θ = 97.8° – with the addition of the –NH functional group in the molecule, as confirmed by attenuated total reflectance Fourier‐transform infrared spectroscopy ( v = 1555 cm −1 ). The tensile strength of bioplastic increases with chitosan content, proving its greater rigidity compared to bioplastic without chitosan. Additionally, the fastest biodegradation rate (9 days) occurs in the composition with high amounts of cassava in a ratio of 6:4 (cassava:chitosan). The bioplastic produced in this study readily decomposes in the environment, making it more sustainable, eco‐friendlier, and providing an alternative to mitigate the use of single‐use thermoplastics.
Journals
2025 EN
Nawaz Haq · Aosaf Rimsha · Nawaz Mubashir
+5 more
ABSTRACT Chemical modification of starches has been proved to improve their physical, functional, and biological characteristics for manufacturing environment‐friendly biodegradable materials of industrial and biomedical importance. Response‐surface optimization of native Nelumbo nucifera starch‐glutaraldehyde crosslinking was performed to synthesize a biodegradable material for industrial, environmental, and biomedical applications. A five‐level tri‐factorial central composite design consisting of three process variables Χ 1 : native starch concentration (NSC), Χ 2 : β‐glutaraldehyde concentration (BGAC), and Χ 3 : stirring time (S t ), was constructed using response‐surface methodology. The CLS was subjected to its physical, functional, and biological characterization. The extraction yield of native starch at various levels of the selected variables was 52.98% ± 2.14%, while the yield of cross‐linked starch (CLS) was 48.22% ± 24.4%. However, the optimum yield of CLS calculated from the employed model (56.37%) was observed at NSC: 0.911 g, BGAC: 0.759%, and S t : 11.180 h. The CLS showed oval‐shaped granules with smooth surfaces; improved crystallinity and thermal stability; good tensile strength (62.86 MPa); elongation at break (33.26%); relatively lower water holding (108% ± 9.67%), swelling (104.59% ± 2.86%), and higher oil holding (136% ± 9.45%) capacities; good biodegradability patterns (46.22% ± 6.01%); and considerable antibacterial activity (zone of inhibition: 13.5 mm against Escherichia coli ). Based on these characteristics, CLS would be preferable for manufacturing environment‐friendly packing materials and biomedical equipment.
Journals
2025 EN
Ibrahim Haruna · Wardeh George · Fares Hanaa
+1 more
Abstract This paper investigates the post‐cracking behavior of mortars reinforced with synthetic polypropylene fibers. To three series of mortars, normal strength (NSM), high strength (HSM), and high strength with fly ash (HSMFA), short and long, was introduced at 0.6% and 1% by volume, respectively. Pre‐notched 4 × 4 × 16 cm were used for 3‐point flexural tests, and the digital image correlation (DIC) method was employed to assess the load‐CMOD curves. Based on the experimental curves, a tri‐linear stress‐crack opening ( σ ‐w) relationship was used to develop an analytical model for the Mode I crack propagation, and the inverse analysis method was applied to optimize the model's parameters. The obtained parameters were compared to the fib MC2010 characteristic values related to serviceability and ultimate limit states. The results show that short fiber‐reinforced mortars exhibit a softening behavior regardless of the fiber dosage after a rapid drop once the tensile strength has been achieved. The three mortars incorporating long fiber reinforcement exhibit a very high deformation capacity and hardening behavior. For NSM, fibers appear to be more effective than HSM and HSMFA. All materials achieve the ultimate fracture opening of 2.5 mm, as defined by the fib MC2010, except 0.6% long fiber‐reinforced HSMFA. Compared to the reference mixture (mixture without fibers), adding synthetic fibers to the mortar did not exhibit a significant environmental and health impact.
WILEY‐VCH Verlag GmbH & Co. KGaA
Journals
2025 EN
Zeyad Abdullah M. · Bayagoob Khaled H. · Amin Mohamed
+3 more
Abstract This study examines the effect of incorporating olive waste ash (OWA) into high‐strength geopolymer concrete (HSGC) by partially replacing fly ash (FA) and/or granulated blast furnace slag (GBFS) in the presence of rice husk ash (RHA). A total of 18 different mixtures were prepared and divided into three groups: (1) Utilizing OWA as a partial replacement for FA at a weight ratio of 10%–50%. (2) Incorporating OWA as a partial substitute for GBFS, with a weight ratio of 10%–50%. (3) Incorporate OWA as a partial substitute for FA and GBFS, with a recommended weight ratio of 10%–50%. The slump flow test was used to analyze the fresh properties of the HSGC. The hardening properties were examined by measuring the compressive strength, tensile strength, flexural strength, and modulus of elasticity. Furthermore, an analysis was conducted on the water absorbency, sulfate attack, and chloride penetration depth. A scanning electron microscope was used for the microstructural analysis. The inclusion of OWA in HSGC mixtures resulted in a significant enhancement of the compressive strength. Specifically, adding 20% OWA to FA increased the compressive strength by 8.9% at 28 days. Similarly, 30% OWA for GGBS and 30% OWA for GGBS + FA led to compressive strength improvements of 20% and 17.8%, respectively. OWA application resulted in an enhanced microstructure density of the HSGC samples. The ideal substitution ratio varied between 20% and 30% based on weight.
WILEY‐VCH Verlag GmbH & Co. KGaA
Journals
2025 EN
Mohamed Ali Abdelrahim · Ali Osama · Metwally Ibrahim M.
Abstract The present article aims to study the behavior of RC columns under blast loading. A nonlinear dynamic Three‐Dimensional (3D) Finite Element FE model‐based explicit solver available in ABAQUS Software is used. A parametric study is investigated to enhance the blast resistance of RC columns under three different scaled distances z of an explosion, that is, 0.23, 0.5, and 1.07 m/kg 1/3 for close, intermediate, and Far in‐distance. In addition, three levels of concrete grades are used, which are Normal Strength Concrete (NSC), High Strength Concrete (HSC), and Ultra High‐Performance Concrete (UHPC). The study also considers Three reinforcement ratios for longitudinal and transverse reinforcement ratios of ( ρ L = 1.28%, 2.4%, and 3.1%) and ( ρ s = 0.6%, 0.9%, and 1.35%), respectively. Further, three different Axial Load Ratios, ALR = 0.01, 0.2, and 0.4, are considered to examine the effect of increasing ALR on the RC column under close explosion. For more investigation, the parametric analysis considers two geometrical shapes of RC columns (square and circular). The material behaviors of concrete and reinforcing steel bars are represented using Concrete Damage Plasticity (CDP) and Johnson–Cook (J–C) models, respectively, available in ABAQUS Software. The FE model has been initially validated against experimental study. The FE‐predicted deflection and damage were observed and agreed with the practical cases. In addition, the parametric study's results demonstrate that the RC column's blast deflection is significantly reduced with increasing reinforcement ratios. However, increasing concrete grade could efficiently reduce blast damage and deflection. Furthermore, compared with NSC, UHPC significantly reduced maximum damage and deflection by around 60% for square and 55% for circular columns, respectively.
WILEY‐VCH Verlag GmbH & Co. KGaA
Journals
2025 EN
Mahmoud Alaa A. · ElSayed Alaa A. · Aboraya Ayman M.
+6 more
Abstract In the current study, the impact of utilizing granite and marble construction waste powders as replacements (1%–9%) for cement on concrete compressive strength was investigated. In the second stage of the experimental program, combined mixtures were designed to evaluate their response to high temperatures using various machine learning (ML) techniques. Models employing water cycle algorithm (WCA) and genetic algorithms (GA) were developed based on 288 experimental results, featuring input variables such as temperature, exposure time, waste powder type, and cement replacement ratio, with residual compressive strength (RCS) as the sole output. Artificial neural networks (ANN), fuzzy logic (FL), and multiple linear regression (MLR) models were also developed for comparison. Optimal performance, with a 22% increase in compressive strength at 28 days, was observed by replacing 9% of cement with waste granite powder (WGP). At high temperatures, the best performance occurred with 9% WGP + 5% waste marble powder (WMP), resulting in a 59.6% increase in RCS value after exposure to 800°C for 2 h. The predictive WCA model outperformed GA and MLR, closely aligning with ANN and FL models, with a mean absolute error of 3.96 kg/cm 2 . Additionally, nonlinear prediction equations of RCS with high regression values were successfully developed using WCA and GA. Furthermore, sensitivity analyses were conducted using the weights of the hidden layers of the idealized neural networks and revealed that the RCS value exhibits high sensitivity to temperature variations. Exposure time had the second‐highest impact on RCS value, followed by the WGP ratio, and then the WMP ratio.
WILEY‐VCH Verlag GmbH & Co. KGaA
Journals
2025 EN
Oukaili Nazar · Allawi Abbas A. · Issa Musa AbdulMuttalib
+4 more
Abstract This study investigated the shear performance of concrete beams with GFRP stirrups vs. traditional steel stirrups. Longitudinal glass fiber‐reinforced polymer (GFRP) bars were used to doubly reinforce the tested beams at both the top and bottom of their cross sections. To accomplish this, several stirrup spacings were provided. Eight beam specimens, measuring 300 × 250 × 2400 mm, were used in an experimental program to test under a two‐point concentrated load with an equal span‐to‐depth ratio until failure. Four beams in Group I have standard mild steel stirrups of 8 mm diameter, while four beams in Group II have GFRP stirrups with the same adopted diameter. The difference between the beams in each group was mainly due to the spacing between the reinforcing stirrups in the constant shear and pure bending spans. The test matrix consists of two beams with shear reinforcement equally distributed at 100 mm and 200 mm in constant shear and pure bending spans, respectively. Stirrups were placed uniformly over the whole effective span of the other six beams. In two beams, stirrups were placed 100 mm apart; in the other two, 75 mm; and in the last two, 50 mm. Test outcomes showed that GFRP stirrups, as opposed to steel stirrups, decreased the ultimate load by around 8%–27% based on stirrup spacing, while reducing the stirrup spacing increased the shear capacity. Also, the presence of compression GFRP bars and GFRP stirrups in the pure bending span led to an increase in the flexural stiffness of the tested beams. Consequently, this increase contributed to a higher ductility index. Accordingly, it is essential to prioritize adequate shear strength above flexural strength when designing GFRP‐reinforced concrete beams, as evidenced by the continuous observation of flexure‐shear cracking as the primary mode of failure in almost all tested beams.
WILEY‐VCH Verlag GmbH & Co. KGaA
Journals
2025 EN
Tijani Ibrahim A. · Dauda Jamiu A. · Kareem Mutiu A.
+1 more
Abstract This study presents a novel, interpretable machine learning framework for predicting the maximum pull load of fiber‐reinforced polymer (FRP) bonded to concrete substrates. A comprehensive test database comprising 983 datasets was gathered from relevant existing studies. The datasets include key input parameters such as concrete compressive strength, bond length, width of FRP sheet, width of concrete block, FRP thickness, and elastic modulus of FRP sheets, with the maximum pull load as the output parameter. Utilizing this curated database, a symbolic regression model based on genetic programming (GP) was developed to uncover the nonlinear relationships among critical variables including axial stiffness of FRP, bond length, and concrete compressive strength. The model's predictive performance was evaluated using standard regression metrics, achieving mean absolute error (MAE) and root mean square error (RMSE) values below 5 kN, mean absolute percentage error (MAPE) slightly above 10%, and coefficient of determination ( R 2 ) exceeding 0.90 on both training and testing datasets. These results confirm the model's accuracy and generalizability. Unlike black‐box models, symbolic regression offers an explicit mathematical expression, ensuring transparency and interpretability for engineering applications. To facilitate practical deployment, a user‐friendly graphical user interface (GUI) named MaxPLoad‐FRP‐Concrete‐GPaided‐PredictionModel was developed, enabling practitioners to input key design parameters and obtain immediate, interpretable predictions. This tool serves as a valuable decision‐support system in the structural design and quality control for FRP‐strengthened concrete structures.
WILEY‐VCH Verlag GmbH & Co. KGaA
Journals
2025 EN
Junaid M. Talha · Alateyat Aroob · Ibrahim Basil
+3 more
Abstract Fiber‐reinforced polymer (FRP) bars are increasingly used in construction due to their high strength‐to‐weight ratio and resistance to corrosion. Despite these advantages, existing design codes for FRP‐reinforced concrete columns (FRP‐RCC) lack comprehensive equations that adequately account for factors such as slenderness, eccentricity, and the contribution of FRP bars to axial capacity. This study addresses these gaps by proposing an artificial neural network (ANN) model to accurately predict the axial capacity of short, slender, concentric, and eccentric FRP‐RCCs. A comprehensive database of 490 column samples from the literature was utilized to analyze the factors influencing FRP‐RCC behavior, develop the ANN model, and validate its performance. The database also enabled a detailed evaluation of current design codes, existing ANN models, and other design equations, comparing their predictive capabilities to the proposed ANN. The results demonstrate the effectiveness of the proposed ANN model, achieving an R 2 value of 0.93 during training and testing and 0.97 during verification with an independent dataset. These findings underscore the model's robustness and practical applicability in engineering design. Furthermore, comparative analysis revealed that the proposed ANN consistently outperforms existing design equations and available ANN models, highlighting its superior predictive accuracy and potential as a reliable tool for designing FRP‐reinforced concrete structures.
WILEY‐VCH Verlag GmbH & Co. KGaA